| Literature DB >> 32837844 |
Kraichat Tantrakarnapa1, Bhophkrit Bhopdhornangkul2, Kanchana Nakhaapakorn3.
Abstract
Aim: A novel corona virus disease 2019 (COVID-19) was declared as pandemic by WHO as global level and local levels in many countries. The movement of people might be one influencing factor, this paper aims to report the situation COVID-19 and spreading in Thailand, including influencing factors of spreading and control. Subject and method: Infected, confirmed COVID-19 data were obtained from the official website of the Department of Disease Control, Ministry of Public Health. Tourist data was downloaded from Ministry of Tourism and Sports. Researchers analyzed the situation from the first found case in Thailand until 15 April 2020 with the timeline of important influencing factors. Correlation coefficients of tourist data and infected case was calculated by person correlation coefficient.Entities:
Keywords: COVID-19; Disease spreading; Influencing factors; Thailand; Tourist factors
Year: 2020 PMID: 32837844 PMCID: PMC7301627 DOI: 10.1007/s10389-020-01329-5
Source DB: PubMed Journal: Z Gesundh Wiss ISSN: 0943-1853
Statistical data of COVID-19 in Thailand as of April 15, 2020
| Item | Thailand | Global | ||
|---|---|---|---|---|
| Number | Percent of total accumulate case | Number | Percent of total accumulate case | |
| New daily confirmed case | 43 | 1.63 | 16,694 | 0.83 |
| New daily death case | 3 | 0.11 | 998 | 0.05 |
| Accumulate Death | 43 | 1.63 | 127,598 | 6.33 |
| Critical case | 61 | 51,527 | 2.56 | |
| Accumulate discharge (recovered case) | 1497 | 56.64 | 491,498 | 24.40 |
| Accumulate confirmed case | 2643 | – | 2,014,554 | |
Source:https://ddcportal.ddc.moph.go.th/portal/apps/opsdashboard/index.html#/20f3466e075e45e5946aa87c96e8ad65
Fig. 1Timeline of important event for COVID-19 spreading and control in Thailand up to April 14, 2020
Fig. 2Percentages of infected COVID-19 cases in Thailand
Fig. 3Distribution of COVID-19 cases in Thailand (source of data: Disease control department, Ministry of Public Health)
Pearson coefficient of correlations between COVID-19 case and the visitor information
| Parameter | Number of overnight staying in province (2019) | Number of visitors 2019 | Number of Thai visitors 2019 | Number of the foreigner visitors 2019 | Generated income in province 2019 | Generated from Thai tourists 2019 | Generated from foreigner tourists 2019 | COVID-19 case |
|---|---|---|---|---|---|---|---|---|
| Number of overnight staying in province (2019) | 1 | |||||||
| Number of visitors 2019 | .968** | 1 | ||||||
| Number of Thai visitors 2019 | .897** | .967** | 1 | |||||
| Number of the foreigner visitors 2019 | .959** | .934** | .812** | 1 | ||||
| Generated income in province 2019 | .958** | .913** | .791** | .980** | 1 | |||
| Income generated from Thai tourists 2019 | .947** | .976** | .943** | .913** | .902** | 1 | ||
| Income generated from foreigner tourists 2019 | .908** | .833** | .682** | .951** | .984** | .810** | 1 | |
Note: Pearson correlation coefficient (** p value <0.01)